Chris Seiffert

Artificial Intelligence · 2008–2010

A researcher in the Science corpus: 2 papers; trusts 14 researchers and is trusted by 3 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 17 citations into it; #26,481 of 35,345 by trust here, #17,412 by citations
• Statistical Learning Theory — 9 citations into it

Whom Chris Seiffert trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Nitesh V. Chawla
2. Yoav Freund
3. Foster J. Provost
4. William W. Cohen
5. Jason Van Hulse
6. Arthur U. Asuncion
7. Robert E. Schapire
8. C. Drummond
9. Kevin W. Bowyer
10. Tom Fawcett

Who trusts Chris Seiffert overall

1. Taghi M. Khoshgoftaar
2. Paula Branco
3. Chakkrit Kla Tantithamthavorn
4. K. Ruwani
5. Mikel Galar
6. Octavio Loyola-González
7. Alberto Fernández
8. Joffrey L. Leevy
9. Marc-Andre Carbonneau
10. Victoria López

Papers from Chris Seiffert's perspective

Ordered by how strongly the researchers Chris Seiffert trusts endorse each paper. Same corpus, a different order for every researcher.

1. Fast Effective Rule Induction
2. UCI Repository of machine learning databases
3. SMOTE: Synthetic Minority Over-sampling Technique
4. Robust Classification for Imprecise Environments
5. Evaluating boosting algorithms to classify rare classes: comparison and improvements (Proceedings 2001 IEEE International Conference on Data Mining)
6. Experiments with a New Boosting Algorithm
7. Gradient-based learning applied to document recognition
8. The Foundations of Cost-Sensitive Learning
9. C4.5, Class Imbalance, and Cost Sensitivity: Why Under-Sampling beats Over-Sampling
10. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)

Their papers

• RUSBoost: A Hybrid Approach to Alleviating Class Imbalance (2010) — 1,761 citations
• RUSBoost: Improving classification performance when training data is skewed (2008) — 295 citations